Atopic Dermatitis and Hospitalization for Mental Health Disorders in the United States
Bibliographic record
Abstract
Little is known about mental health (MH) emergencies in atopic dermatitis (AD) and their financial burden. We sought to determine hospitalization rates and costs of MH disorders in AD patients. We analyzed data from the Nationwide Inpatient Sample from 2002 to 2012, containing a representative 20% sample of US hospitalizations. Overall, 835 AD (1.36%) and 2,434,703 non-AD (0.75%) patients had a primary admission for an MH disorder. Atopic dermatitis patients admitted for MH disorders were more likely to be younger, Asian, of black race, and in a higher income quartile and have an increasing number of chronic conditions. In multivariable logistic regression models adjusting for demographics, AD was associated with a primary admission for MH disorders in adults, including mood disorders, schizophrenia, and developmental disorders. Atopic dermatitis was not associated with a primary admission for an MH disorder in children. There were an estimated US $183,821,629 excess costs of care annually for MH disorders in inpatients with versus without AD. In conclusion, AD was associated with higher odds of hospitalization for all MH disorders and substantial excess costs of inpatient care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".